What does Digital Twin mean?

A digital twin is a virtual replica of a real object or system that stays connected to its original through continuous measurement data. It continuously reflects the current state and makes it possible to simulate planned changes before anyone implements them on the actual asset. What sets it apart from an ordinary simulation model is precisely this constant feedback loop with reality.

Three components make it up: the model with its geometry and behavioral rules, the data connection through sensors or specialist applications, and an evaluation layer that detects deviations. The sensors feed values such as temperature, pressure, flow, or occupancy into the model. Simulations then run through individual scenarios, such as a component failing under full load. Depending on the application, updates happen anywhere from every few seconds to every few days.

A digital twin pays off wherever interventions are expensive or risky and cannot simply be tried out during live operation. Typical examples include heat, water, and power supply networks, production facilities, and the building technology of larger properties. For systems without sensors, an ordinary model is all that is possible, because the feedback loop is missing.

The advantage over planning based on experience is that decisions rest on measured states rather than estimates. Variants can be compared computationally without touching operations. Deviations between model and measurement also reveal exactly where a facility behaves differently than assumed.

Without measurement points, a twin depicts a facility that does not actually exist in that form. The starting question is therefore always which sensors are in place and how well they are maintained. For critical infrastructure, the model data needs the same protection as the facility itself.